Demonstration of low cost automation solutions for SME adoption of digital manufacturing
< Project overview >
The goal of this project is to address a common industrial concern that recent developments in digital manufacturing are unlikely to be accessible by SMEs owing to the associated capital cost of upgrading industrial computing and communication environments.
Hence, proposing an approach focused on the exploitation of open source, low-cost and off-the-shelf technologies for IoT, mobile computing and sensing while developing demonstrators to assess solutions and collect feedback from manufacturing SME organisations.
In order to deliver this project, the implementation of digital solutions for manufacturing (demonstrators) were proposed to address the following barriers:
Lack of knowledge on how to deploy low-cost IoT systems.
Lack of understanding of the full landscape of possible architectures for a possible IoT solution.
Lack of understanding in how IoT will/can generate value in a given application domain.
What was done?
The main activities this project focussed on were:
Proving how low-cost, off-the-shelf and open source IoT technologies can be adopted to enable digital capabilities in manufacturing SMEs.
Exploring and documenting a short guide to systematically build industrial IoT applications, ie from conception to implementation while involving a manufacturing sector stakeholder.
This project has successfully delivered six demonstrators within the manufacturing domain. Specifically, these demonstrators focussed on digital devices for part identification and tracking; condition monitoring; job specification and production cell monitoring. The technical document produced in this project was employed as part of a roadmap activity to help identify and expand the business domain of Bulgin, a leading manufacturer of environmentally sealed connectors and components.
Deliverables and outputs
1. Low-cost programmable logic controller
This system uses a small single-board computer prepared to execute programmable logic controller (PLC) logic for enabling industrial robot operations (see figure 1). Specifically, the single-board computer is a Raspberry Pi (RPi) augmented with a Pimoroni Automation pHAT board to enable 24v signal bits communication to/from a Fanuc robot controller, ie the native control system for the Fanuc M-6i Anthropomorphic robot.
The pHAT board is supplied with an open source library capable to deal with all the necessary input and output functions. As a result, this RPi-based robotic system demonstrates that the industrial robot can be controlled in much the same fashion as with the traditional PLC but using low-cost IoT platform hardware and open source libraries instead.
Figure 1. Low-cost industrial robot controller setup with a Raspberry Pi augmented with an automation board.
2. Real-time production cell information access
This demonstrator uses a small single-board computer which monitors a PLC deployed within a production cell (see figure 2). In particular, the operating system of a RPi has been converted to a real-time one using the Xenomai library.
In order to establish network communication, the RPi was also patched with the IgH EtherCAT library. Therefore, providing the right level of communication to request and report the current status of a production cell. As a result, this RPi-based EtherCAT system demonstrates the use a low-cost IoT platform hardware to access production environments without unnecessary interruptions.
Figure 2. Real-time production cell information access system setup with a Raspberry Pi patched with real-time and EtherCAT libraries to access a Beckhoff PLC network.
3. Low-cost monitoring system
This monitoring system was deployed on a fused deposition modelling (FDM) Ultimaker 2 3D printer considered a ‘prosumer’ unit at the higher end of the consumer market, therefore making a good testbed for our purpose. This printing device comes with native thermistors in the printer head and the heated print platform, thus enabling temperature reading and control. In addition, the 3DP was retrofitted with a low-cost 3-axis analogue accelerometer connected to a RPi and two RPi cameras (see figure 3).
The accelerometer is fixed to the printer head, the first camera is positioned to take the final snapshot of the part piece whereas the second camera records the layer-by-layer part piece while printing. All these generate data which is largely stored in a cloud-based purpose-built time series database (InfluxDB). As a result, this system demonstrates the combination of low-cost, off -the-shelf and open source IoT sensing technologies to deliver a monitoring bolt-on system.
Figure 3. Low-cost bolt-on monitoring system retrofitted in a 3D printer with sensors, cameras and Raspberry Pi.
4. QR code inventory tracking
This low-cost inventory tracking system was built to simultaneously scan and identify supplier parts arriving either alone or in a tray. In particular, it was realised using a RPi camera and image processing libraries for QR code recognition. In this way, when trays or individual parts are positioned under the camera, the QR code recognition triggers a back office query to retrieve information related to stock levels and locations. Therefore, recommending the user a place to store the recognised items and updating the associated stock levels.
The back office system offers other types of searches and image recognition capabilities through an interactive graphical user interface. This system demonstrates the integration of low-cost, off-the-shelf and open source IoT computing platform technologies to enable part identification and tracking.
Figure 4. QR code inventory tracking system setup with a vision system deployed in a Raspberry Pi.
5. Digital job cards
This description of a work system was built with the objective to provide the requirements for – and capture the results of – the current job activities of a manufacturing operator. This demonstrator replaces the typical paper-based job cards, hence bringing online key information related to jobs, parts and operator activities such as part, workstation and operator identification; sequence of operations with their associated conditions, status and duration; part defects, reworks and inspections; workstation set-up, etc (see figure 6).
It was realised using Django for content management, Pyzbar library for QR code generation and SQLite for data storing. This system demonstrates the combination of open source and off-the-shelf software technologies to collect and record online the most typical manufacturing activities observed on a shop floor.
Figure 5. Digital job cards system built with off-the-shelf open source software libraries.
6. Mini-project final report template v1.3.1 6. Industrial IoT capabilities
This is a document presenting a technical overview on the key software and hardware elements used for developing IoT applications. Its content comprises six sections: IoT conceptualisation, sensors technology, communication technologies, reference architectures, industrial IoT development kits, IoT ecosystems and IoT in industry.
The first section gives an overarching picture of how to idealise IoT applications as well as the elements considered within IoT applications. The second section enlarges on definitions and fundamental properties of sensors. The third section expands on the existing communication capabilities and guidelines for selection. The fourth section gives two examples of hardware technologies currently employed for rapid prototyping and development. The fifth section depicts the most relevant IoT ecosystems available in the market while the last section enumerates different domains where IoT applications have been successfully deployed.
The impact this project had centres on general public engagement activities and sector stakeholder engagement activities. The general public engagement activities involved:
Showcasing the QR code inventory tracking demonstrator in the Advanced Engineering Show at the National Exhibition Centre, Birmingham, on 30–31 October 2019.
An IoT challenge for the IEEE Students Hackathon organised by the 2019 IEEE International Workshop on Metrology for Industry 4.0 and IoT, at the University of Naples, Federico II.
A two-day hackathon event organised for students of the University of Cambridge, at the Institute for Manufacturing, on 26–27 October 2019.
The sector stakeholder engagement activities involved:
Demonstrators showcase to participant companies and other industrial delegates in workshops organised at the Institute for Manufacturing, University of Cambridge.
A half day workshop dedicated to define a roadmap for Bulgin product innovation. In this particular activity, Bulgin was looking to understand and explore the elements of software and hardware needed when building IoT capabilities.
As a result of the project outcomes, further foreseen activities will centre on:
Providing both research and technical support for the EPSRC project ‘Digital Manufacturing on a Shoestring’. In particular, these activities will centre on how to define, identify and classify best suited hardware and software technologies.
Providing both research and technical support for the Pitch-In project ‘IoT-based devices for non-critical support in hospitals’. In particular, these activities will centre on how to adapt and translate existing IoT demonstrators developed for manufacturing into non life-critical medical devices.
This project has demonstrated how manufacturing SMEs could gain access to digital manufacturing capabilities by building six digital low-cost IoT solutions while showcasing its outcomes and transferring knowledge through public engagement activities. As a result, this University has benefited from:
Exposing students and academics to a novel methodology for prototyping digital manufacturing capabilities.
Having a guide to systematically explore the elements of software and hardware needed to deliver IoT applications.
Broadcasting our approach for building digital manufacturing capabilities through different sectors of the manufacturing community.
This project has demonstrated the use of off-the-shelf, low-cost and open source IoT technologies for developing digital solutions for manufacturing SMEs. Therefore, having had an opportunity to deploy any of the demonstrators in a SME, it would have been beneficial to measure the practical impact of our approach as well as to assess several technical aspects such as the integration complexity with already existing systems, user experience or solution robustness against an SME production pace.
One of the key aspects of this research project was its underpinning interdisciplinary approach. Therefore, having the ability to collaborate with related research programmes, eg those exploiting low-cost, off-the-shelf, open source IoT technologies on different domains or those looking at digitally enhancing legacy manufacturing equipment would have been useful to both validate our methodology and knowledge exchange.
Access to deliverables, resources and media content
The shareable resources of this project can be found at:
What has Pitch-In done for you?
The results of this Pitch-In programme has been crucial to help quick start the EPSRC Digital Manufacturing on a Shoestring project since it has enabled an initial exploration of IoT technologies to deliver proof-of-concept demonstrators for low-cost digital manufacturing capabilities.
Professor Duncan McFarlane – University of Cambridge